MR Fingerprint requires an
exhaustive search in a dictionary, which even for moderately sized problems,
becomes costly and possibly intractable. In this work, we propose an
alternative approach: instead of an exhaustive search for every signal, we use
the dictionary to learn the functional relationship between signals and parameters.
This allows the direct estimation of parameters without the need of searching through
the dictionary. The comparison between a standard grid search and the proposed
approach suggest that MR Fingerprinting could benefit from a regression
approach to limit dictionary size and fasten computation time.

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